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An increasingly-widely accepted conclusion in economics (especially in the context of rapidly industrializing countries) is that in the last twenty or twenty-five years technological growth has been biased in favour of high-skilled workers - that is, the changes have made high-skilled workers more productive relative to low-skilled workers. Most people think this is primarily driven by greater computerization and automation, which replaces several (low-skill) workers doing relatively repetitive tasks with a single (high-skill) worker managing machinery that performs those tasks. (In this context, we’re basically defining your skill level as the number of years of education you’d need before you could start at the job. This is not really what “skill” means but in this context that’s what I’m talking about.)
This isn’t necessarily a bad thing, as it can raise everyone’s wages and overall standard of living (including low-skilled workers), but it does mean that wages are going to rise fastest for higher-skilled workers. Without policy intervention, this leads to sharply rising income inequality.
Anyway, I’m trying to write a paper on the role of certain kinds of infrastructure in skill-biased technological growth, but for the statistical end of things I need to come up with a good index for how much of the technological growth favours high-skilled workers over low-skilled, or vice versa. There’s obviously no one definite way to measure this, so I have to be sneaky and find something persuasive.
The standard way to deal with this is to use data from the United Nations Industrial Development Organization, and basically use the proportion of manufacturing wages which go to management, engineering staff, and other white-collar employees (as opposed to people who actually work in production) as a proxy for the premium on skilled labour. Unfortunately, the relevant data set ends in the early 1990s, and also I’m not entirely sure the white-collar/blue-collar divide accurately captures the premium on skilled labour. Like, I’m entirely willing to believe that a technician at a pharmaceutical plant might have had to spend way more time and money acquiring their skills than a manager at a meat-packing plant, you know? So, for this paper I’m going to be coming up with a new measure of skill-biased technological change.
It works something like this: I’m going to take existing measures of how R&D-intensive various manufacturing sectors are, and for each country in each year I’m going to regress the share of total manufacturing wages on the level of R&D intensiveness. If the level of R&D intensiveness shows a positive year-on-year shift, then that’s a sign that technological change is biased towards high-skilled workers. If it’s basically the same every year, then that’s a sign that technological change is affecting everyone more or less equally.
Does this sound like a reasonable measure? Or is it unconvincing to associate R&D intensiveness with the level of skill associated with manufacturing? (For what it’s worth, the ordering looks pretty reasonable, with high-precision manufacturing like aerospace at the top and relatively bulk goods like textiles near the bottom.) As always, feedback is appreciated.
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